{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b6e37b19",
   "metadata": {},
   "source": [
    "# Project Agent: working with a repository\n",
    "\n",
    ">>> TODO writeup: write a paragraph to explain what \"Explorative Repository Agent\" is.\n",
    "\n",
    "Author: Runlong Zhou, Beibin Li\n",
    "\n",
    "\n",
    "- Motivation: TODO writeup\n",
    "- Warm-Start: we warm start the repo by reading some important files and architectures, and then summarize the findings inside the \"SUMMARY.txt\".\n",
    "- **NOTE**: we have not utilize any truncking or caching mechanism yet to save computational cost. So, the OpenAI API cost would be high if you use this code base. Please proceed with caution.\n",
    "\n",
    "Timeline\n",
    "- July, 2023: The original project idea and [code](https://github.com/BeibinLi/SPM/commit/d18392d5ffabdf1af621f392619bf9d0ce031437) are created during Runlong's 2023 summer internship at Microsofot Research. During the project, we used \"long-term\" and \"short-term\" external memory inside LLM agents to store and retrieve useful information. \n",
    "- August, 2023: We create the [Coffee Dataset](https://github.com/BeibinLi/Coffee_Roasting_Dataset) as a synthetic benchmark for supply chain products. \n",
    "- January, 2024: we re-implemented the pipeline with [AutoGen](https://github.com/microsoft/autogen) and included the research code into [OptiGuide](https://github.com/microsoft/OptiGuide). We also provide a simpler design without utilizing external memory mechanism. \n",
    "\n",
    "\n",
    "\n",
    "\n",
    "### Introduction: Why do we need exploration\n",
    "TODO writeup\n",
    "\n",
    "\n",
    "### Methodology: Warm-Start Summarization\n",
    "TODO writeup\n",
    "\n",
    "\n",
    "### Related Work\n",
    "The idea in this notebook is similar to [GPT Code Interpreter](https://openai.com/blog/chatgpt-plugins), [InterCode](http://arxiv.org/abs/2306.14898), [Open Interpreter](https://github.com/KillianLucas/open-interpreter), and many other open source projects. Here, we provide a subset of important inspirations, because it is hard (and almost impossible) to provide an exhaustive list of related projects. \n",
    "\n",
    "Prior Work:\n",
    "- LLM: [Recursive summarization](http://arxiv.org/abs/2109.10862), \n",
    "- Prompting guidelines: [ReAct](https://arxiv.org/abs/2210.03629), [CoT](https://proceedings.neurips.cc/paper_files/paper/2022/hash/9d5609613524ecf4f15af0f7b31abca4-Abstract-Conference.html)\n",
    "- LLM Tools: [AutoGen](https://github.com/microsoft/autogen), LangChain, AutoGPT, LlamaIndex\n",
    "\n",
    "Some concurrent studies:\n",
    "- Code editing: [Magicoder](http://arxiv.org/abs/2312.02120). [RepoAgent](https://github.com/LOGIC-10/RepoAgent)\n",
    "- Exploration with LLMs: [Explore-Instruct](http://arxiv.org/abs/2310.09168), [search engine with copilot](http://arxiv.org/abs/2311.01235)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0678f35",
   "metadata": {},
   "source": [
    "### Installing this experimental notebook\n",
    "\n",
    "Install the explorer branch of OptiGuide:\n",
    "```bash\n",
    "pip install https://github.com/microsoft/OptiGuide/archive/explore.zip\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7e342c38",
   "metadata": {},
   "outputs": [],
   "source": [
    "import autogen\n",
    "from optiguide.experimental.explorer import ProjectAgent\n",
    "from autogen import UserProxyAgent\n",
    "import os\n",
    "\n",
    "config_list_gpt4 = autogen.config_list_from_json(\n",
    "    \"OAI_CONFIG_LIST\",\n",
    "    filter_dict={\n",
    "        \"model\": [\"gpt-4\", \"gpt-4-0314\", \"gpt4\", \"gpt-4-32k\", \"gpt-4-32k-0314\", \"gpt-4-32k-v0314\"],\n",
    "    },\n",
    ")\n",
    "\n",
    "\n",
    "config_list_gpt3 = autogen.config_list_from_json(\n",
    "    \"OAI_CONFIG_LIST\",\n",
    "    filter_dict={\n",
    "        \"model\": [\"gpt-35-turbo\", \"gpt-3.5-turbo\"],\n",
    "    },\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd832416",
   "metadata": {},
   "source": [
    "## Example: Coffee Dataset\n",
    "\n",
    "We use the [Coffee Dataset](https://github.com/BeibinLi/Coffee_Roasting_Dataset) as the example application, where users\n",
    "\n",
    "\n",
    "```bash\n",
    "git clone https://github.com/BeibinLi/Coffee_Roasting_Dataset ~/\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "946825de",
   "metadata": {},
   "outputs": [],
   "source": [
    "repo_loc = os.path.expanduser(\"~/Coffee_Roasting_Dataset/opti_coffee/\")\n",
    "assert os.path.exists(repo_loc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9b7e5525",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0b46274a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0baff83e",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mData copied to temporary directory: /home/beibinli/OptiGuide/notebook/tmpak2w_cwy\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "Read files, understand the repo, and summarize the knowledge in 500 words.\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: I need to explore the content of the files within the repository to summarize the knowledge contained in it.\n",
      "ACTION:\n",
      "```sh\n",
      "ls\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "database\n",
      "internal\n",
      "public\n",
      "solver\n",
      "visualization\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: I need to explore the contents of each top-level directory to understand what type of information each contains.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "ls database\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "cafe.csv\n",
      "demand_history.csv\n",
      "employee.csv\n",
      "roastery_2010.csv\n",
      "roastery_2011.csv\n",
      "roastery_2012.csv\n",
      "roastery_2013.csv\n",
      "roastery_2014.csv\n",
      "roastery_2015.csv\n",
      "roastery_2016.csv\n",
      "roastery_2017.csv\n",
      "roastery_2018.csv\n",
      "roastery_2019.csv\n",
      "roastery_2020.csv\n",
      "roastery_2021.csv\n",
      "roastery_2022.csv\n",
      "roastery_2023.csv\n",
      "sell_price_history.csv\n",
      "supplier.csv\n",
      "supply_price_history.csv\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: The `database` directory contains various CSV files that provide data regarding the company's operations. I will examine one of these files to gather further details.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "cat database/employee.csv\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "name,date_of_birth,position,date_of_hire,salary,performance_rating,site,city,country\n",
      "Margot-Alex Millet,1995-05-16,Roaster,2022-03-23,45485,Excellent,1,Paris,France\n",
      "Élodie Salmon,1958-09-23,Manager,2022-04-26,45544,Excellent,1,Paris,France\n",
      "Yves Peltier-Delmas,1972-02-01,Cashier,2023-05-14,25335,Good,1,Paris,France\n",
      "Julien Philippe-Faivre,1965-09-07,Roaster,2020-09-16,54335,Poor,1,Paris,France\n",
      "林 陽子,1983-12-28,Barista,2020-12-26,28048,Poor,2,Tokyo,Japan\n",
      "石井 裕美子,1971-01-05,Cashier,2023-07-19,24066,Excellent,2,Tokyo,Japan\n",
      "鈴木 太郎,1976-05-05,Accountant,2021-08-04,76595,Poor,2,Tokyo,Japan\n",
      "井上 香織,1985-02-21,Cashier,2022-09-03,25211,Average,2,Tokyo,Japan\n",
      "田中 千代,1968-10-13,Accountant,2023-02-11,62779,Average,2,Tokyo,Japan\n",
      "小川 拓真,1965-11-29,Accountant,2020-07-29,65636,Average,2,Tokyo,Japan\n",
      "佐藤 稔,1983-09-10,Manager,2022-06-14,69273,Average,2,Tokyo,Japan\n",
      "斎藤 知実,1964-07-14,Manager,2021-09-01,55301,Good,2,Tokyo,Japan\n",
      "石川 学,1971-07-05,Accountant,2021-02-05,62357,Excellent,2,Tokyo,Japan\n",
      "吉田 京助,1961-10-25,Manager,2020-07-02,63818,Excellent,2,Tokyo,Japan\n",
      "Richard Baker,1973-07-12,Cleaner,2022-10-09,27509,Good,3,Sydney,Australia\n",
      "John Webb,2001-04-03,Roaster,2020-05-15,40863,Average,3,Sydney,Australia\n",
      "Nathan Wright,1974-04-22,Cashier,2022-11-04,26156,Poor,3,Sydney,Australia\n",
      "Jean Conway,1998-10-17,Manager,2023-06-13,55965,Poor,3,Sydney,Australia\n",
      "Logan Fleming,1966-01-13,Cleaner,2021-02-04,29471,Excellent,3,Sydney,Australia\n",
      "Ryan Medina,1985-03-23,Manager,2023-07-27,57389,Average,3,Sydney,Australia\n",
      "Timothy Nguyen,1979-02-25,Manager,2023-06-29,55571,Average,3,Sydney,Australia\n",
      "Richard Adkins,1976-08-02,Barista,2022-09-18,28798,Average,3,Sydney,Australia\n",
      "Steve Schmidt,1983-06-10,Roaster,2020-08-07,41989,Excellent,3,Sydney,Australia\n",
      "Diogo Mendes,1988-09-14,Cleaner,2020-07-09,29423,Poor,4,Rio de Janeiro,Brazil\n",
      "Maria Clara Dias,1973-06-28,Cleaner,2023-05-28,25975,Average,4,Rio de Janeiro,Brazil\n",
      "Evelyn Martins,1982-11-14,Cashier,2021-08-12,25517,Good,4,Rio de Janeiro,Brazil\n",
      "Eduarda Gomes,1986-04-25,Cashier,2022-11-10,22876,Good,4,Rio de Janeiro,Brazil\n",
      "Donald Flores,1983-10-26,Cashier,2020-06-08,24967,Good,5,Cairo,Egypt\n",
      "Gabrielle Rogers,1986-11-21,Cleaner,2022-02-18,27980,Good,5,Cairo,Egypt\n",
      "Robin Gordon,1966-07-30,Roaster,2020-04-29,48037,Excellent,5,Cairo,Egypt\n",
      "Michelle Jordan,1978-08-08,Barista,2022-12-04,31784,Poor,5,Cairo,Egypt\n",
      "William Copeland,1963-04-23,Accountant,2020-06-26,65051,Excellent,5,Cairo,Egypt\n",
      "Laura Reese,1971-03-01,Accountant,2021-04-07,86036,Average,5,Cairo,Egypt\n",
      "Emily Martin,1977-04-25,Cashier,2023-05-12,22545,Excellent,5,Cairo,Egypt\n",
      "Christina Taylor,2003-02-26,Cleaner,2022-02-02,33131,Excellent,5,Cairo,Egypt\n",
      "Robert Hull,1978-06-09,Cleaner,2020-03-23,29581,Good,5,Cairo,Egypt\n",
      "James Malone,1998-01-13,Manager,2021-08-09,56691,Poor,5,Cairo,Egypt\n",
      "Heidi Gfeller,1972-08-11,Manager,2023-04-11,48832,Poor,6,Zurich,Switzerland\n",
      "Raimund Wolf,1964-04-23,Accountant,2023-07-06,75466,Poor,6,Zurich,Switzerland\n",
      "Laurin Mettler,1959-05-08,Cashier,2022-04-26,23035,Poor,6,Zurich,Switzerland\n",
      "Danijel Hofer,1966-03-18,Cleaner,2021-01-16,34592,Average,6,Zurich,Switzerland\n",
      "Enis Leunberger-Winkler,1987-09-05,Accountant,2022-02-08,87468,Average,6,Zurich,Switzerland\n",
      "Angelika Schweizer,1967-10-10,Cashier,2021-04-14,25580,Good,6,Zurich,Switzerland\n",
      "Birgit Flückiger,2000-10-27,Accountant,2020-01-18,60279,Excellent,6,Zurich,Switzerland\n",
      "Daniel Burns,1964-01-05,Cashier,2023-03-09,24825,Poor,7,Seattle,United States\n",
      "Mrs. Jennifer Lewis,1979-06-16,Roaster,2020-06-11,48327,Average,7,Seattle,United States\n",
      "Steven Lester,1980-09-07,Barista,2022-12-07,27974,Average,8,Ann Arbor,United States\n",
      "Alejandra Dunn,1982-01-18,Barista,2021-09-13,31497,Excellent,8,Ann Arbor,United States\n",
      "Jonathan Stewart,1980-04-09,Cashier,2020-09-02,24756,Poor,8,Ann Arbor,United States\n",
      "William Rich,1991-09-17,Roaster,2022-03-28,48757,Average,8,Ann Arbor,United States\n",
      "Joseph Holt,1986-11-14,Cleaner,2021-10-13,33533,Excellent,8,Ann Arbor,United States\n",
      "Barbara Brown,2001-10-12,Cleaner,2020-12-22,31934,Poor,8,Ann Arbor,United States\n",
      "Lauren Thomas,1970-02-17,Cashier,2023-03-13,24895,Excellent,8,Ann Arbor,United States\n",
      "Belinda Baker,1985-07-02,Manager,2020-04-14,49575,Poor,8,Ann Arbor,United States\n",
      "Kathleen Hanna,1975-03-12,Roaster,2020-11-12,46653,Poor,8,Ann Arbor,United States\n",
      "Stephen Boyd,1997-03-25,Manager,2021-09-27,72018,Average,8,Ann Arbor,United States\n",
      "Andrea Holland,1992-07-23,Barista,2022-11-18,27007,Poor,9,New Haven,United States\n",
      "Tina Singh,1977-05-26,Manager,2020-10-01,41933,Average,9,New Haven,United States\n",
      "Daniel Phillips,2004-01-12,Cashier,2021-07-21,24261,Poor,9,New Haven,United States\n",
      "Scott Huff,1995-09-22,Barista,2022-03-18,28296,Good,9,New Haven,United States\n",
      "Aarav Talwar,1981-08-25,Cashier,2022-08-31,25422,Excellent,10,Mumbai,India\n",
      "Pranay Gopal,1983-07-02,Barista,2021-11-15,22935,Excellent,10,Mumbai,India\n",
      "Miraya Balakrishnan,1997-10-19,Roaster,2020-03-09,43017,Excellent,10,Mumbai,India\n",
      "Amaya Doménech-Campoy,2000-04-24,Cashier,2020-01-21,26240,Excellent,11,Havana,Cuba\n",
      "Purificación Gibert Godoy,1962-05-22,Cleaner,2020-09-23,35472,Average,11,Havana,Cuba\n",
      "Bárbara Pastora Villar Heredia,1970-08-05,Cleaner,2020-08-28,32831,Good,11,Havana,Cuba\n",
      "Yésica Checa Puig,1965-04-30,Roaster,2020-09-29,40687,Average,11,Havana,Cuba\n",
      "Reyes Julie Melero Cabeza,1965-08-22,Manager,2020-10-04,55174,Excellent,11,Havana,Cuba\n",
      "Febe Morán,1974-08-27,Barista,2023-06-18,23278,Good,11,Havana,Cuba\n",
      "Anacleto del Hidalgo,1984-08-09,Roaster,2022-09-03,42900,Good,11,Havana,Cuba\n",
      "Evamaria Löffler,1979-03-24,Manager,2022-08-24,56652,Average,12,Berlin,Germany\n",
      "Dr. Aloys Weimer B.Sc.,2002-12-02,Barista,2021-08-22,24841,Excellent,12,Berlin,Germany\n",
      "Klaus-D. Tintzmann,1996-10-10,Accountant,2022-01-16,69488,Poor,12,Berlin,Germany\n",
      "Karen Morris,1965-06-14,Accountant,2020-12-13,66552,Poor,13,Cape Town,South Africa\n",
      "Brandon Ball,1965-10-15,Barista,2020-07-08,23429,Good,13,Cape Town,South Africa\n",
      "Linda Harvey,1965-10-16,Manager,2021-06-08,45965,Excellent,13,Cape Town,South Africa\n",
      "Mark Kramer,2004-05-12,Barista,2020-01-15,28113,Poor,13,Cape Town,South Africa\n",
      "Nicole Garza DVM,1972-10-16,Manager,2020-09-06,64161,Good,13,Cape Town,South Africa\n",
      "Adam Harris,1960-09-30,Cashier,2020-01-05,25877,Poor,13,Cape Town,South Africa\n",
      "Garry Cunningham,2001-06-19,Cleaner,2020-05-05,31860,Good,14,London,United Kingdom\n",
      "Dr Colin Reynolds,1957-09-28,Accountant,2022-02-12,86637,Excellent,14,London,United Kingdom\n",
      "Kelly Wright,2001-11-15,Barista,2021-08-31,29197,Average,14,London,United Kingdom\n",
      "陈红梅,1960-08-12,Barista,2020-11-02,27414,Good,15,Beijing,China\n",
      "陈桂珍,1962-07-08,Cleaner,2023-02-22,25553,Average,15,Beijing,China\n",
      "赵帆,1990-08-02,Manager,2020-09-29,63468,Poor,15,Beijing,China\n",
      "Cecilia Schlosser,1997-04-28,Cashier,2022-04-02,22346,Good,16,Vienna,Austria\n",
      "Nora Leitner,2004-03-14,Cleaner,2020-12-18,29922,Excellent,16,Vienna,Austria\n",
      "刘凤兰,1971-02-27,Roaster,2023-05-31,45639,Excellent,17,Taipei,China\n",
      "陈楠,2005-04-17,Cashier,2021-07-28,26435,Excellent,17,Taipei,China\n",
      "赵利,1961-06-12,Manager,2022-04-04,56117,Average,17,Taipei,China\n",
      "吴杰,1986-03-24,Manager,2020-03-09,73397,Good,17,Taipei,China\n",
      "الدكتورة ابتكار بنو الدئل,2004-09-08,Cashier,2020-11-19,23469,Excellent,18,Marrakech,Morocco\n",
      "المهندس صعب الكلغاصي,1959-09-04,Cashier,2023-01-01,26436,Average,18,Marrakech,Morocco\n",
      "جميلة غوشة,1989-11-28,Roaster,2023-01-26,57020,Poor,18,Marrakech,Morocco\n",
      "Λεονάρδος Κίσσας,1981-03-20,Manager,2022-03-03,57084,Poor,19,Athens,Greece\n",
      "Ιπποκράτης Ρέντζος,1957-12-28,Cleaner,2020-05-27,26144,Average,19,Athens,Greece\n",
      "Εριφύλη Λιόντη,1982-06-25,Barista,2022-05-05,24595,Excellent,19,Athens,Greece\n",
      "Βλασία Σκούμπρου,1972-11-15,Roaster,2022-01-25,40367,Excellent,19,Athens,Greece\n",
      "Θεοδότη Κουτσοβίδου,1991-08-06,Cashier,2020-08-12,25128,Good,19,Athens,Greece\n",
      "Βιολέτα Κωστοπούλου,1965-06-15,Barista,2020-10-28,29016,Poor,19,Athens,Greece\n",
      "郝红梅,1977-06-13,Roaster,2022-02-06,45423,Excellent,20,Shenzhen,China\n",
      "王华,1976-02-08,Barista,2020-07-24,30733,Average,20,Shenzhen,China\n",
      "Tiziana Peruzzi,1980-06-27,Barista,2021-11-01,22567,Poor,21,Rome,Italy\n",
      "Anita Ponti,1964-07-03,Accountant,2021-10-14,65990,Poor,21,Rome,Italy\n",
      "Ruggiero Ceschi,1984-03-22,Cleaner,2020-10-27,30025,Average,21,Rome,Italy\n",
      "Dott. Serena Cilea,1959-11-12,Manager,2021-10-18,48698,Average,21,Rome,Italy\n",
      "Atenulf Alfieri,1995-12-04,Manager,2022-11-16,55753,Good,21,Rome,Italy\n",
      "Giovanna Pennetta,1987-07-26,Cashier,2021-04-09,24961,Excellent,21,Rome,Italy\n",
      "Annamaria Petrocelli-Biagiotti,1997-04-13,Cashier,2021-06-23,26111,Poor,21,Rome,Italy\n",
      "Francesco Ficino,1996-10-21,Cashier,2022-09-03,22220,Excellent,21,Rome,Italy\n",
      "Sig. Benvenuto Nicolucci,1985-12-21,Accountant,2020-08-17,75825,Poor,21,Rome,Italy\n",
      "Prof. Hanim Zorlu Akgündüz,1966-07-06,Accountant,2022-06-24,64588,Average,22,Istanbul,Turkey\n",
      "Ortak Yılmaz,1965-12-03,Cashier,2023-05-03,24340,Good,22,Istanbul,Turkey\n",
      "Köker Fırat,2001-01-08,Manager,2021-12-15,52011,Poor,22,Istanbul,Turkey\n",
      "Hilayda İldeş Demirel,2003-10-24,Barista,2022-07-19,29155,Average,22,Istanbul,Turkey\n",
      "Akar Yorulmaz,1973-06-25,Cleaner,2021-10-22,31526,Poor,22,Istanbul,Turkey\n",
      "Korkmazalp Başok Türk Eraslan,1962-09-10,Cleaner,2021-05-01,28857,Poor,22,Istanbul,Turkey\n",
      "İldem Pehlil Mansız Akça,2002-06-21,Manager,2021-12-12,48954,Excellent,22,Istanbul,Turkey\n",
      "Okt. Vacibe Güngören Manço Şama,1976-03-24,Cashier,2020-11-08,24357,Poor,22,Istanbul,Turkey\n",
      "Cavit Güçlü,1980-09-08,Cashier,2021-02-27,22365,Excellent,22,Istanbul,Turkey\n",
      "Lucas Benjamin Carmela Rodriguez,1993-01-07,Cleaner,2022-01-28,28450,Excellent,23,Buenos Aires,Argentina\n",
      "Luna Luna Garcia Martin,1992-06-19,Manager,2021-12-23,69462,Excellent,23,Buenos Aires,Argentina\n",
      "Thiago Ezequiel Santiago Garcia Hernandez,1957-09-25,Barista,2021-02-04,25243,Good,23,Buenos Aires,Argentina\n",
      "Guillermina Luciano Rodriguez Figueroa,1996-03-13,Barista,2023-01-17,29916,Poor,23,Buenos Aires,Argentina\n",
      "Dr(a). Tomàs Torres,1960-06-25,Cashier,2021-05-15,24208,Average,23,Buenos Aires,Argentina\n",
      "Sr(a). Agustín Gomez,1961-04-28,Barista,2023-02-08,22096,Average,23,Buenos Aires,Argentina\n",
      "Sr(a). Tomas Correa,1975-03-12,Roaster,2023-04-01,44874,Poor,23,Buenos Aires,Argentina\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: Now I have an understanding of the structure and contents of the `database` directory, which seems to include data about the company's cafes, employees, and sales, among other aspects. I need to explore the other top-level directories to form a comprehensive summary. Next, I will explore the `internal` directory to understand the kind of information it contains about the company's internal affairs.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "ls internal\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "Employee Benefits.md\n",
      "Financial Plan.md\n",
      "Manual%3A How to Negotiate with Coffee Bean Suppliers and Cafe Shops.md\n",
      "Marketing Strategies.md\n",
      "Quality Control Manuals.md\n",
      "Roast Manual.md\n",
      "safety.md\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: I will read one of the internal documents to understand the type of internal knowledge and documentation the company maintains.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "cat internal/Employee Benefits.md\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 1 (execution failed)\n",
      "Code output: \n",
      "cat: internal/Employee: No such file or directory\n",
      "cat: Benefits.md: No such file or directory\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: It seems that there was an error due to the space in the file name. I will use quotes around the file name to correctly reference it and try to read the contents again.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "cat internal/\"Employee Benefits.md\"\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "Employee Benefits\n",
      "\n",
      "Table of Content:\n",
      "\n",
      "Here is the current outline:\n",
      "1 Introduction\n",
      "1.1 Company Overview\n",
      "1.2 Employee Benefits Importance\n",
      "\n",
      "2 Employee Health and Wellness\n",
      "2.1 Health Insurance\n",
      "2.2 Mental Health Support\n",
      "\n",
      "3 Financial Benefits\n",
      "3.1 Retirement Plans\n",
      "3.2 Employee Stock Options\n",
      "\n",
      "4 Work-Life Balance\n",
      "4.1 Flexible Work Schedules\n",
      "4.2 Paid Time Off\n",
      "\n",
      "5 Professional Development\n",
      "5.1 Training and Education Programs\n",
      "5.2 Career Advancement Opportunities\n",
      "\n",
      "6 Employee Recognition and Rewards\n",
      "6.1 Performance-Based Bonuses\n",
      "6.2 Employee Appreciation Events\n",
      "\n",
      "7 Workplace Environment\n",
      "7.1 Collaborative and Supportive Culture\n",
      "7.2 Employee Assistance Programs\n",
      "\n",
      "8 Conclusion\n",
      "8.1 Summary of Employee Benefits\n",
      "8.2 Commitment to Employee Satisfaction\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "1 Introduction\n",
      "\n",
      "At Opti Coffee Roasting Company, we understand that our employees are the backbone of our success. As a company founded on passion and dedication to the craft of coffee, we recognize the importance of fostering a positive and supportive work environment for our team members. In this document, we will outline the comprehensive employee benefits package that we have designed to ensure the well-being, satisfaction, and growth of our employees.\n",
      "\n",
      "\n",
      "\n",
      "1.1 Company Overview\n",
      "\n",
      "Opti Coffee is a Seattle-based coffee roasting company that prides itself on sourcing, roasting, and serving the finest coffee from around the world. Founded in 2010 by two coffee enthusiasts, Jake and Mia, our company has grown from a small garage-based roastery to a thriving business with a loyal following of local customers. Our commitment to quality and craftsmanship has been the driving force behind our success, and we believe that investing in our employees is essential to maintaining this standard.\n",
      "\n",
      "\n",
      "\n",
      "1.2 Employee Benefits Importance\n",
      "\n",
      "We recognize that providing a competitive and comprehensive employee benefits package is crucial for attracting and retaining top talent in the coffee industry. Our benefits program is designed to support the physical, mental, and financial well-being of our employees, as well as to promote a healthy work-life balance and opportunities for professional growth. By offering a range of benefits that cater to the diverse needs of our team members, we aim to create a workplace where employees feel valued, motivated, and empowered to contribute to the success of Opti Coffee.\n",
      "\n",
      "In the following sections, we will provide an overview of the various employee benefits offered at Opti Coffee Roasting Company, including health and wellness programs, financial benefits, work-life balance initiatives, professional development opportunities, employee recognition and rewards, and our commitment to fostering a collaborative and supportive workplace environment.\n",
      "\n",
      "\n",
      "\n",
      "2 Employee Health and Wellness\n",
      "\n",
      "At Opti Coffee, we believe that a healthy and happy workforce is essential for maintaining productivity and fostering a positive workplace culture. Our health and wellness benefits are designed to support the physical and mental well-being of our employees, ensuring that they have access to the resources and support they need to maintain a healthy lifestyle.\n",
      "\n",
      "\n",
      "\n",
      "2.1 Health Insurance\n",
      "\n",
      "We offer comprehensive health insurance coverage to our employees, including medical, dental, and vision plans. Our goal is to provide our team members with peace of mind, knowing that their health and the health of their families are well taken care of.\n",
      "\n",
      "\n",
      "\n",
      "2.2 Mental Health Support\n",
      "\n",
      "In addition to physical health benefits, we also recognize the importance of mental health and well-being. We provide resources and support for employees to access mental health services, such as counseling and therapy, to help them manage stress and maintain a healthy work-life balance.\n",
      "\n",
      "\n",
      "\n",
      "3 Financial Benefits\n",
      "\n",
      "Opti Coffee is committed to supporting the financial well-being of our employees by offering a range of financial benefits, including retirement plans and employee stock options. These benefits are designed to help our team members build long-term financial security and share in the success of the company.\n",
      "\n",
      "\n",
      "\n",
      "3.1 Retirement Plans\n",
      "\n",
      "Opti Coffee offers retirement plans to help our employees build long-term financial security and prepare for their future. By providing these benefits, we aim to support our team members in achieving their financial goals and ensuring a comfortable retirement.\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "3.2 Employee Stock Options\n",
      "\n",
      "In addition to retirement plans, Opti Coffee also offers employee stock options as part of our financial benefits package. This program allows our team members to share in the success of the company and benefit from its growth. By providing employee stock options, we aim to foster a sense of ownership and commitment among our employees, further strengthening our company's foundation for continued success.\n",
      "\n",
      "\n",
      "4 Work-Life Balance\n",
      "\n",
      "We understand the importance of maintaining a healthy work-life balance and offer flexible work schedules and paid time off to help our employees achieve this balance. By providing these benefits, we aim to create a workplace where employees can thrive both professionally and personally.\n",
      "\n",
      "\n",
      "\n",
      "4.1 Flexible Work Schedules\n",
      "\n",
      "Opti Coffee recognizes the importance of accommodating the diverse needs and lifestyles of our employees. As part of our commitment to promoting a healthy work-life balance, we offer flexible work schedules that allow our team members to manage their personal and professional responsibilities effectively. By providing this flexibility, we aim to create a supportive and inclusive workplace environment where employees can thrive and contribute to the success of the company.\n",
      "\n",
      "\n",
      "\n",
      "4.2 Paid Time Off\n",
      "\n",
      "In addition to flexible work schedules, Opti Coffee also offers paid time off to help our employees maintain a healthy work-life balance. We understand the importance of taking time away from work to rest, recharge, and attend to personal matters. Our paid time off policy ensures that our team members have the opportunity to take the necessary breaks they need without worrying about financial implications. By providing this benefit, we aim to create a workplace where employees feel valued and supported in their pursuit of both personal and professional fulfillment.\n",
      "\n",
      "\n",
      "5 Professional Development\n",
      "\n",
      "Opti Coffee is dedicated to the growth and development of our employees. We offer training and education programs, as well as career advancement opportunities, to help our team members reach their full potential and contribute to the success of the company.\n",
      "\n",
      "\n",
      "\n",
      "5.1 Training and Education Programs\n",
      "\n",
      "Opti Coffee is committed to the ongoing professional development of our employees. We offer a variety of training and education programs designed to help our team members enhance their skills, stay current with industry trends, and advance their careers within the company. By providing these opportunities, we aim to foster a culture of continuous learning and growth, ensuring that our employees are well-equipped to contribute to the success of Opti Coffee and maintain our high standards of quality and craftsmanship in the coffee industry.\n",
      "\n",
      "\n",
      "5.2 Career Advancement Opportunities\n",
      "\n",
      "In addition to training and education programs, Opti Coffee also offers career advancement opportunities for our employees. We believe in recognizing and rewarding hard work, dedication, and talent, and we are committed to providing our team members with the chance to grow within the company. By offering these opportunities, we aim to create a workplace where employees feel motivated to excel in their roles and contribute to the ongoing success of Opti Coffee. This approach not only benefits our employees but also ensures that our company continues to thrive and maintain its reputation for excellence in the coffee industry.\n",
      "\n",
      "\n",
      "6 Employee Recognition and Rewards\n",
      "\n",
      "We believe in recognizing and rewarding the hard work and dedication of our employees. Through performance-based bonuses and employee appreciation events, we aim to create a culture of recognition and appreciation that motivates and inspires our team members.\n",
      "\n",
      "\n",
      "\n",
      "6.1 Performance-Based Bonuses\n",
      "\n",
      "At Opti Coffee, we believe in rewarding our employees for their hard work and dedication to the company. One way we do this is through performance-based bonuses, which provide financial incentives for employees who meet or exceed their performance goals. By offering these bonuses, we aim to create a culture of recognition and appreciation that motivates our team members to continually strive for excellence in their roles. This approach not only benefits our employees but also contributes to the overall success and growth of Opti Coffee, as we continue to uphold our high standards of quality and craftsmanship in the coffee industry.\n",
      "\n",
      "\n",
      "\n",
      "6.2 Employee Appreciation Events\n",
      "\n",
      "In addition to performance-based bonuses, Opti Coffee also hosts employee appreciation events as a way to recognize and celebrate the hard work and dedication of our team members. These events provide an opportunity for employees to come together, socialize, and enjoy a well-deserved break from their daily responsibilities. By organizing these events, we aim to foster a sense of camaraderie and belonging among our employees, further strengthening the supportive and collaborative workplace culture that we strive to maintain at Opti Coffee.\n",
      "\n",
      "Through these employee appreciation events, we demonstrate our gratitude for the contributions our team members make to the success of the company and reinforce our commitment to their well-being and satisfaction. We believe that by investing in our employees in this way, we are not only creating a positive work environment but also ensuring the continued growth and success of Opti Coffee in the competitive coffee industry.\n",
      "\n",
      "\n",
      "\n",
      "7 Workplace Environment\n",
      "\n",
      "At Opti Coffee, we are committed to fostering a collaborative and supportive workplace environment. Our employee assistance programs and supportive culture ensure that our employees have the resources and support they need to succeed in their roles and contribute to the success of the company.\n",
      "\n",
      "\n",
      "\n",
      "7.1 Collaborative and Supportive Culture\n",
      "\n",
      "At Opti Coffee, we believe that a collaborative and supportive workplace culture is essential for the success of our company and the well-being of our employees. We strive to create an environment where team members feel comfortable sharing their ideas, asking for help, and working together to achieve common goals. By fostering this type of culture, we aim to promote open communication, mutual respect, and a sense of shared purpose among our employees.\n",
      "\n",
      "In addition to the benefits of collaboration and support in the workplace, this culture also contributes to the overall satisfaction and engagement of our employees. When team members feel valued and supported, they are more likely to be motivated, productive, and committed to the success of the company. This, in turn, helps to ensure that Opti Coffee continues to thrive and maintain its reputation for excellence in the coffee industry.\n",
      "\n",
      "By prioritizing a collaborative and supportive workplace culture, we are not only investing in the well-being and satisfaction of our employees but also laying the foundation for the continued growth and success of Opti Coffee. We believe that by working together and supporting one another, our team members can achieve their full potential and contribute to the ongoing success of our company.\n",
      "\n",
      "\n",
      "7.2 Employee Assistance Programs\n",
      "\n",
      "In addition to fostering a collaborative and supportive workplace culture, Opti Coffee also offers employee assistance programs (EAPs) to provide our team members with the resources and support they need to navigate various challenges they may face in their personal and professional lives. These programs are designed to help employees address a wide range of issues, such as stress management, financial planning, and family matters, among others.\n",
      "\n",
      "By offering EAPs, we aim to create a workplace environment where employees feel supported and empowered to seek help when they need it. We understand that our team members may encounter various challenges throughout their lives, and we believe that providing access to these resources can help them better manage these situations and maintain their well-being.\n",
      "\n",
      "Furthermore, we recognize that when employees are able to effectively address and manage personal challenges, they are more likely to be engaged, productive, and satisfied in their roles. This, in turn, contributes to the overall success and growth of Opti Coffee, as we continue to uphold our high standards of quality and craftsmanship in the coffee industry.\n",
      "\n",
      "In conclusion, our employee assistance programs are an integral part of our commitment to supporting the well-being and satisfaction of our team members. By providing these resources and fostering a collaborative and supportive workplace culture, we aim to create a positive work environment where employees can thrive and contribute to the ongoing success of Opti Coffee.\n",
      "\n",
      "\n",
      "8 Conclusion\n",
      "\n",
      "In summary, Opti Coffee Roasting Company is dedicated to providing a comprehensive employee benefits package that supports the well-being, satisfaction, and growth of our team members. We believe that by investing in our employees, we are investing in the future success of our company and maintaining our commitment to quality and craftsmanship in the coffee industry.\n",
      "\n",
      "\n",
      "8.1 Summary of Employee Benefits\n",
      "\n",
      "In summary, Opti Coffee Roasting Company offers a comprehensive employee benefits package designed to support the well-being, satisfaction, and growth of our team members. Our benefits program encompasses various aspects of our employees' lives, including health and wellness, financial security, work-life balance, professional development, and recognition and rewards.\n",
      "\n",
      "Our health and wellness benefits include comprehensive health insurance coverage, as well as mental health support resources, ensuring that our employees have access to the care they need to maintain their physical and mental well-being. Financial benefits, such as retirement plans and employee stock options, are designed to help our team members build long-term financial security and share in the success of the company.\n",
      "\n",
      "To promote a healthy work-life balance, we offer flexible work schedules and paid time off, allowing our employees to effectively manage their personal and professional responsibilities. Professional development opportunities, including training and education programs and career advancement options, are provided to help our team members reach their full potential and contribute to the success of Opti Coffee.\n",
      "\n",
      "Finally, our employee recognition and rewards program, which includes performance-based bonuses and employee appreciation events, aims to create a culture of recognition and appreciation that motivates and inspires our team members. In addition, our commitment to fostering a collaborative and supportive workplace environment, along with our employee assistance programs, ensures that our employees have the resources and support they need to succeed in their roles and contribute to the success of the company.\n",
      "\n",
      "By offering this comprehensive employee benefits package, we aim to create a workplace where employees feel valued, motivated, and empowered to contribute to the success of Opti Coffee. We believe that by investing in our employees, we are investing in the future success of our company and maintaining our commitment to quality and craftsmanship in the coffee industry.\n",
      "\n",
      "\n",
      "8.2 Commitment to Employee Satisfaction\n",
      "\n",
      "At Opti Coffee Roasting Company, our commitment to employee satisfaction is at the core of our company values. We believe that by investing in our employees and providing them with a comprehensive benefits package, we are not only creating a positive work environment but also ensuring the continued growth and success of our company in the competitive coffee industry.\n",
      "\n",
      "Our commitment to employee satisfaction is demonstrated through our various employee benefits, which are designed to support the well-being, growth, and work-life balance of our team members. By offering health and wellness benefits, financial security options, flexible work schedules, professional development opportunities, and recognition and rewards programs, we aim to create a workplace where employees feel valued, motivated, and empowered to contribute to the success of Opti Coffee.\n",
      "\n",
      "In addition to our employee benefits package, our commitment to fostering a collaborative and supportive workplace culture further contributes to employee satisfaction. By promoting open communication, mutual respect, and a sense of shared purpose among our employees, we create an environment where team members can thrive and excel in their roles.\n",
      "\n",
      "Furthermore, our employee assistance programs provide our team members with the resources and support they need to navigate various challenges they may face in their personal and professional lives. By offering these programs, we demonstrate our dedication to the well-being and success of our employees, both inside and outside of the workplace.\n",
      "\n",
      "In conclusion, our commitment to employee satisfaction is a driving force behind the success of Opti Coffee Roasting Company. By investing in our employees and providing them with the support and resources they need to thrive, we are not only creating a positive work environment but also ensuring the continued growth and success of our company in the coffee industry. We believe that by working together and supporting one another, our team members can achieve their full potential and contribute to the ongoing success of Opti Coffee.\n",
      "\n",
      "\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: I've explored the `database` and `internal` directories, gaining insights into employee data and internal documentation on employee benefits. I will continue to explore the remaining directories such as `public`, `solver`, and `visualization` by listing their contents to understand the breadth of data and documents available.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "ls public\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "contact_info.md\n",
      "newsletter\n",
      "our_company.md\n",
      "service_and_price.md\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: I will now explore the `public` directory further by listing the contents of the `newsletter` subdirectory to understand the type of public communications the company issues.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "ls public/newsletter\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "2021 Apr\n",
      "2021 Feb\n",
      "2021 Jun\n",
      "2021 Mar\n",
      "2021 May\n",
      "newsletter.md\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: I will read the `newsletter.md` file to get a sense of the content and style of the company's public newsletters.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "cat public/newsletter/newsletter.md\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "Newsletter\n",
      "\n",
      "Stay updated with the latest news and events from Opti Coffee, the award-winning coffee roasting company that delivers the finest beans and blends to your cup.\n",
      "\n",
      "Awards\n",
      "\n",
      "- Opti Coffee wins gold medal at the Specialty Coffee Association Roaster Competition. (April 15, 2021, by John Smith)\n",
      "- Opti Coffee's Ethiopia Yirgacheffe named one of the best coffees of the year by Coffee Review. (March 10, 2021, by Jane Doe)\n",
      "- Opti Coffee's Colombia Supremo earns the Rainforest Alliance Certified seal for its environmental and social standards. (February 5, 2021, by Mark Lee)\n",
      "\n",
      "Praises\n",
      "\n",
      "- \"Opti Coffee is a shining example of how to roast coffee with passion, skill, and integrity. Their coffees are complex, balanced, and delicious, and their service is impeccable.\" - James Hoffman, author of The World Atlas of Coffee. (May 20, 2021, by James Hoffman)\n",
      "- \"Opti Coffee has a knack for finding and showcasing the best flavors and aromas of each origin and blend. Their coffees are always fresh, consistent, and satisfying, and their staff is friendly and knowledgeable.\" - Liz Clayton, editor of Sprudge. (April 25, 2021, by Liz Clayton)\n",
      "- \"Opti Coffee is one of my favorite roasters in the country. Their coffees are smooth, rich, and nuanced, and their roasting style is respectful of the terroir and the farmers. I highly recommend their subscription service, which delivers a curated selection of their coffees every month.\" - Kevin Sinnott, host of Coffee Con. (March 30, 2021, by Kevin Sinnott)\n",
      "\n",
      "Future Plans\n",
      "\n",
      "- Opti Coffee announces the opening of its new flagship store in downtown Chicago, featuring a state-of-the-art roastery, a spacious cafe, and a coffee education center. (June 1, 2021, by Anna Lee)\n",
      "\n",
      "- Opti Coffee expands its distribution to Canada, Mexico, and Europe, partnering with local retailers and online platforms to bring its coffees to more customers. (May 15, 2021, by David Kim)\n",
      "\n",
      "- Opti Coffee launches its new line of cold brew products, including ready-to-drink bottles, concentrate, and nitro cans, made with its signature blends and natural ingredients. (April 1, 2021, by Sarah Jones)\n",
      "\n",
      "\n",
      "Charities and Contributions\n",
      "\n",
      "- Opti Coffee donates $10,000 to the Coffee Kids program, which supports young coffee farmers in Latin America, Africa, and Asia, by providing them with training, mentorship, and resources. (May 5, 2021, by John Smith)\n",
      "- Opti Coffee participates in the Grounds for Health campaign, which raises awareness and funds for cervical cancer prevention and treatment for women in coffee-growing communities. (April 10, 2021, by Jane Doe)\n",
      "- Opti Coffee joins the 1% for the Planet network, which commits to donating 1% of its annual sales to environmental nonprofits. (March 5, 2021, by Mark Lee)\n",
      "\n",
      "Fiscal Report\n",
      "\n",
      "- Opti Coffee reports a 25% increase in revenue and a 15% increase in profit for the first quarter of 2021, compared to the same period last year. (April 30, 2021, by Anna Lee)\n",
      "- Opti Coffee sees a 40% growth in its online sales and a 30% growth in its subscription service, as more customers opt for home delivery and convenience. (March 31, 2021, by David Kim)\n",
      "- Opti Coffee achieves a 95% customer satisfaction rate and a 90% retention rate, according to its latest survey and feedback. (February 28, 2021, by Sarah Jones)\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: I've examined the `public` directory and have read the `newsletter.md` file for information on the company's public image and outreach. Next, I will look into the `solver` directory to gauge the technical and analytical aspects of the company's operations.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "ls solver\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "cpp\n",
      "cs\n",
      "java\n",
      "main.py\n",
      "Makefile\n",
      "README.md\n",
      "src\n",
      "test\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: Let's read the README.md to understand what the `solver` directory is used for.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "cat solver/README.md\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "This code is a simulation of a coffee distribution network. It reads data from CSV files, creates objects for suppliers, roasteries, cafes, and customers, and optimizes the distribution of coffee from suppliers to roasteries to cafes based on demand and shipping costs.\n",
      "\n",
      "The code starts by importing the necessary classes and modules, including Supplier, Roastery, Cafe, DistributionNetwork, CoffeeDistributionOptimizer, pandas, and pdb. It then reads command line arguments using the argparse module, which allows the user to specify the year, month, and base directory of the database.\n",
      "\n",
      "Next, the code reads the supplier.csv file using the pandas module and creates a dictionary of Supplier objects using the data in the file. Each row in the file represents a supplier, and the columns include the supplier ID, contact name, maximum purchase for the year, city, and phone number.\n",
      "\n",
      "The code then reads the demand_history.csv file, which contains historical demand data for each cafe and coffee product. It filters the data to only include the year and month specified by the user, and creates a dictionary of Cafe objects using the data in the file. Each row in the file represents a demand record, and the columns include the year, month, customer ID, product ID, and quantity.\n",
      "\n",
      "The code also reads the customer.csv file, which contains information about each cafe. It uses this data to set the name, location, and contact information for each Cafe object.\n",
      "\n",
      "The code then calculates the income for the month by reading the sell_price_history.csv file, which contains historical sell prices for each coffee product. It filters the data to only include the year and month specified by the user, and calculates the income for each cafe based on the sell price and demand for each coffee product.\n",
      "\n",
      "Overall, this code provides a framework for simulating a coffee distribution network and optimizing the distribution of coffee based on demand and shipping costs. It uses object-oriented programming principles to create objects for suppliers, roasteries, cafes, and customers, and uses the pandas module to read and manipulate data from CSV files. The CoffeeDistributionOptimizer class can be used to optimize the distribution of coffee based on demand and shipping costs, and the pdb module can be used for debugging.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: I have explored the `database`, `internal`, `public`, and `solver` directories and read some of their key files. The last top-level directory to explore is `visualization`. I'll need to gather information on the types of visualization scripts included.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "ls visualization\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "bean_price.py\n",
      "cpp\n",
      "cs\n",
      "java\n",
      "membership_duration.py\n",
      "salary.py\n",
      "supplier_on_map.py\n",
      "supplier_price.py\n",
      "test\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: To finish the exploration of the repo and gain some insight into the types of visualizations used in the company, I'll read one of the Python visualization scripts.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "cat visualization/bean_price.py\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "import pandas as pd\n",
      "import matplotlib.pyplot as plt\n",
      "import argparse\n",
      "import os\n",
      "\n",
      "def get_args():\n",
      "    parser = argparse.ArgumentParser(description='Plot the range of bean price for a specified bean.')\n",
      "    \n",
      "    parser.add_argument('--name', type=str, default=None, required=True, help='Bean Name, for example Arabica')\n",
      "    \n",
      "    return parser.parse_args()\n",
      "\n",
      "def get_data(bean_name):\n",
      "    # Read the sell_price_history.csv data\n",
      "    df = pd.read_csv('database/sell_price_history.csv')\n",
      "\n",
      "    filtered_data = df[df['source_bean_type'].str.lower() == bean_name]\n",
      "\n",
      "    if filtered_data.shape[0] == 0:\n",
      "        raise ValueError(f'No bean with name {args.name} found.')\n",
      "\n",
      "    # Convert the month and year columns to a single datetime column\n",
      "    filtered_data['date'] = pd.to_datetime(filtered_data['year'].astype(str) + '-' + filtered_data['month'].astype(str) + '-01')\n",
      "\n",
      "    return filtered_data\n",
      "\n",
      "def plot_data(data, bean_name):\n",
      "    # Group by the date and calculate min, max, and mean\n",
      "    grouped_data = data.groupby('date')['price_per_unit'].agg(['min', 'max', 'mean']).reset_index()\n",
      "\n",
      "    # Plot\n",
      "    plt.figure(figsize=(12, 6))\n",
      "\n",
      "    # Fill the region between min and max\n",
      "    plt.fill_between(grouped_data['date'], grouped_data['min'], grouped_data['max'], color='skyblue', alpha=0.4, label='Price Range (Min to Max)')\n",
      "\n",
      "    # Plot mean price\n",
      "    plt.plot(grouped_data['date'], grouped_data['mean'], color='blue', marker='o', label='Mean Price')\n",
      "\n",
      "    plt.title(f'Bean Price Chart for {bean_name}')\n",
      "    plt.xlabel('Time')\n",
      "    plt.ylabel('Price')\n",
      "    plt.legend()\n",
      "    plt.tight_layout()\n",
      "    plt.grid(True, which='both', linestyle='--', linewidth=0.5)\n",
      "\n",
      "    os.makedirs('images', exist_ok=True)\n",
      "    plt.savefig(f\"images/bean_price_{bean_name}.png\")\n",
      "\n",
      "if __name__ == \"__main__\":\n",
      "    args = get_args()\n",
      "\n",
      "    bean_name = args.name.lower()\n",
      "    \n",
      "    data = get_data(bean_name)\n",
      "\n",
      "    plot_data(data, bean_name)\n",
      "    \n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "Based on the files and directories I have explored within the code repository, the following summary can be provided:\n",
      "\n",
      "The code repository is organized into several directories, each encapsulating different facets of the coffee company's operations and public-facing content.\n",
      "\n",
      "The `database` directory contains historical and current data in CSV format, ranging from employee records and cafe data to supply, demand, and sell price histories. This directory is likely used for tracking operational metrics, analyzing business performance, and optimizing supply chain management.\n",
      "\n",
      "The `internal` directory holds important documents related to internal company procedures and policies, such as quality control manuals, financial plans, and a negotiation manual with coffee bean suppliers and cafes. A notable document within this directory is the `Employee Benefits.md`, which details a comprehensive benefits package for employees that focuses on health, financial well-being, professional development, work-life balance, and a supportive workplace environment.\n",
      "\n",
      "The `public` directory showcases the company's public image, including newsletters that highlight company awards, praises from industry influencers, future expansion plans, charitable contributions, and financial performance. This directory serves to maintain transparency with customers and stakeholders and to promote the company's successes and community involvement.\n",
      "\n",
      "The `solver` directory encompasses a simulation of the coffee distribution network. It includes optimization scripts (`main.py`) that read from multiple CSV databases, create objects representing entities within the supply chain such as suppliers and cafes, and optimize the flow of goods based on various parameters. The README file within this directory provides an overview of these processes and outlines the purpose of the optimization code.\n",
      "\n",
      "Lastly, the `visualization` directory contains Python scripts (`bean_price.py`) for creating visual representations of data, such as price trends for different types of coffee beans. These visualizations assist with data analysis and potentially support decision-making or external communications.\n",
      "\n",
      "In summary, the repository combines elements of data management, internal documentation, public relations, supply chain optimization, and data visualization to support the multifaceted operations of the coffee company. It reflects a data-driven approach to managing a complex distribution network while maintaining a focus on the satisfaction of employees and customers through benefits, transparency, and active community engagement.\n",
      "\n",
      "--- TERMINATE ---\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "TERMINATE\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "What programming languages are mainly used in this project?\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: In order to determine the main programming languages used in the project, I will check the directories that contain source code, particularly the `solver` and `visualization` directories, as well as any other directories that may contain source code mentioned in the directory tree.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "ls solver\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "cpp\n",
      "cs\n",
      "java\n",
      "main.py\n",
      "Makefile\n",
      "README.md\n",
      "src\n",
      "test\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: Now I need to see if the directories within `solver` contain source code and identify their respective programming languages.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "ls solver/cs\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "Program.cs\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: I have identified that the `solver/cs` directory contains C# source code. Now I will check the `solver/cpp` directory to identify if it contains C++ source code.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "ls solver/cpp\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "Cafe.h\n",
      "CoffeeDistributionOptimizer.h\n",
      "DistributionNetwork.h\n",
      "main.cpp\n",
      "Roastery.h\n",
      "Supplier.h\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: Following the directory exploration, the main programming languages used in this project are Python, C#, and C++. Now, I will check the `visualization` directory to confirm the languages used for visualization scripts.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "ls visualization\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "bean_price.py\n",
      "cpp\n",
      "cs\n",
      "java\n",
      "membership_duration.py\n",
      "salary.py\n",
      "supplier_on_map.py\n",
      "supplier_price.py\n",
      "test\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: I will now check the `visualization/cpp` directory for C++ and the `visualization/cs` for C# visualization-related source files.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "ls visualization/cpp\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "bean_price.cpp\n",
      "cs\n",
      "java\n",
      "membership_duration.cpp\n",
      "plot_supplier_map.py\n",
      "salary_plot.cpp\n",
      "supplier_city_counts.cpp\n",
      "supplier_price.cpp\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: I've found C++ source files in the `visualization/cpp` directory. Next, I'll look into the `visualization/cs` directory to identify if there are any C# source files related to visualization.\n",
      "\n",
      "ACTION:\n",
      "```sh\n",
      "ls visualization/cs\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is sh)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "BeanPricePlot.cs\n",
      "MembershipDurationPlot.cs\n",
      "SalaryPlot.cs\n",
      "SupplierOnMap.cs\n",
      "SupplierPricePlot.cs\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "The project utilizes multiple programming languages:\n",
      "\n",
      "1. **Python**: Used for creating various scripts, like the ones found in the `visualization` directory (e.g., `bean_price.py`, `membership_duration.py`, `salary.py`, `supplier_on_map.py`, `supplier_price.py`) and the main script in the `solver` directory (`main.py`).\n",
      "\n",
      "2. **C++**: This language is found in both the `solver/cpp` and `visualization/cpp` directories, which contain header (`*.h`) and source files (`*.cpp`), indicating that C++ is used for parts of the project related to optimization and visualization.\n",
      "\n",
      "3. **C#**: Source files with the extension `.cs` in both the `solver/cs` and `visualization/cs` directories suggest that C# is also a language used for developing parts of the project, particularly for some backend operations and visualization aspects.\n",
      "\n",
      "In conclusion, Python, C++, and C# are the main programming languages used in this project. \n",
      "\n",
      "--- TERMINATE ---\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "TERMINATE\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "agent = ProjectAgent(\n",
    "    name=\"Project-Agent\",\n",
    "     root=repo_loc,\n",
    "    max_consecutive_auto_reply=30,\n",
    "    llm_config={\"config_list\": config_list_gpt4, \"seed\": 42},\n",
    "     description=\"\"\n",
    ")\n",
    "\n",
    "user = autogen.UserProxyAgent(\n",
    "    name=\"User_proxy\",\n",
    "    system_message=\"A human admin.\",\n",
    "    human_input_mode=\"NEVER\",  # Try between ALWAYS or NEVER\n",
    "    max_consecutive_auto_reply=0,\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "46e1091b",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6c146ccc",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33mUser_proxy\u001b[0m (to Project-Agent):\n",
      "\n",
      "Read the datbase, and show me the average of employee salary per country.\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "Read the datbase, and show me the average of employee salary per country.\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "REASON: To present the average employee salary per country from the database, I'll execute a Python script to process the 'employee.csv' file.\n",
      "\n",
      "ACTION:\n",
      "```python\n",
      "import pandas as pd\n",
      "\n",
      "# Read CSV data into a DataFrame\n",
      "data = pd.read_csv('database/employee.csv')\n",
      "\n",
      "# Group by 'country' and calculate mean of 'salary'\n",
      "avg_salary_by_country = data.groupby('country')['salary'].mean().reset_index()\n",
      "\n",
      "# Rename the columns for clarity\n",
      "avg_salary_by_country.columns = ['Country', 'Average Salary']\n",
      "\n",
      "# Print the average salary by country\n",
      "print(avg_salary_by_country)\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[31m\n",
      ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001b[0m\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "exitcode: 0 (execution succeeded)\n",
      "Code output: \n",
      "           Country  Average Salary\n",
      "0        Argentina    34892.714286\n",
      "1        Australia    40412.333333\n",
      "2          Austria    26134.000000\n",
      "3           Brazil    25947.750000\n",
      "4            China    43797.666667\n",
      "5             Cuba    36654.571429\n",
      "6            Egypt    42580.300000\n",
      "7           France    42674.750000\n",
      "8          Germany    50327.000000\n",
      "9           Greece    33722.333333\n",
      "10           India    30458.000000\n",
      "11           Italy    41350.000000\n",
      "12           Japan    53308.400000\n",
      "13         Morocco    35641.666667\n",
      "14    South Africa    42349.500000\n",
      "15     Switzerland    50750.285714\n",
      "16          Turkey    36239.222222\n",
      "17  United Kingdom    49231.333333\n",
      "18   United States    36640.062500\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to Repository Environment Agent):\n",
      "\n",
      "The average employee salary per country, extracted from the database, is as follows (in local currency):\n",
      "\n",
      "- Argentina: 34,892.71\n",
      "- Australia: 40,412.33\n",
      "- Austria: 26,134.00\n",
      "- Brazil: 25,947.75\n",
      "- China: 43,797.66\n",
      "- Cuba: 36,654.57\n",
      "- Egypt: 42,580.30\n",
      "- France: 42,674.75\n",
      "- Germany: 50,327.00\n",
      "- Greece: 33,722.33\n",
      "- India: 30,458.00\n",
      "- Italy: 41,350.00\n",
      "- Japan: 53,308.40\n",
      "- Morocco: 35,641.66\n",
      "- South Africa: 42,349.50\n",
      "- Switzerland: 50,750.28\n",
      "- Turkey: 36,239.22\n",
      "- United Kingdom: 49,231.33\n",
      "- United States: 36,640.06\n",
      "\n",
      "Please note that the average salary is specific to the dataset provided and is subject to changes based on data updates in the repository. The currency is not specified and is assumed to be in the local currency of each respective country.\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mRepository Environment Agent\u001b[0m (to Project-Agent):\n",
      "\n",
      "TERMINATE\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mProject-Agent\u001b[0m (to User_proxy):\n",
      "\n",
      "The average employee salary per country, extracted from the database, is as follows (in local currency):\n",
      "\n",
      "- Argentina: 34,892.71\n",
      "- Australia: 40,412.33\n",
      "- Austria: 26,134.00\n",
      "- Brazil: 25,947.75\n",
      "- China: 43,797.66\n",
      "- Cuba: 36,654.57\n",
      "- Egypt: 42,580.30\n",
      "- France: 42,674.75\n",
      "- Germany: 50,327.00\n",
      "- Greece: 33,722.33\n",
      "- India: 30,458.00\n",
      "- Italy: 41,350.00\n",
      "- Japan: 53,308.40\n",
      "- Morocco: 35,641.66\n",
      "- South Africa: 42,349.50\n",
      "- Switzerland: 50,750.28\n",
      "- Turkey: 36,239.22\n",
      "- United Kingdom: 49,231.33\n",
      "- United States: 36,640.06\n",
      "\n",
      "Please note that the average salary is specific to the dataset provided and is subject to changes based on data updates in the repository. The currency is not specified and is assumed to be in the local currency of each respective country.\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "# user.initiate_chat(agent, message=\"Plot the average of employee salary in a global map. Use the data and documents inside the repository.\")\n",
    "user.initiate_chat(agent, message=\"Read the datbase, and show me the average of employee salary per country.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb66588a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7c39f5c6",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "8fe3e56d",
   "metadata": {},
   "source": [
    "## Future Work\n",
    "- Recover the privacy and security features using Docker.\n",
    "- Memory management and efficient prompting (store and retrieve information).\n",
    "- Better serialization to store agents' states.\n",
    "- The agent can create \"pull request\" automatically.\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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